Mixed effects logistic regression models for longitudinal ordinal functional response data with multiple-cause drop-out from the longitudinal study of aging

In the context of analyzing ordinal functional limitation responses from th e Longitudinal Study of Aging, we investigate the association between curre nt functional limitation and previous year's limitation and its modificatio n by physical activity and multiple causes of drop-out. We accommodate the longitudinal nature of the multiple causes of informative drop-out (death a nd unknown loss-to-follow-up) with a mixed effects logistic model. Under th e proposed model with a random intercept and slope, the ordinal functional outcome and multiple discrete time survival profiles share a common random effect structure. This shared parameter selection model assumes that the mu ltiple causes of drop-out are conditionally independent of the functional l imitation outcome given the underlying random effect representing an indivi dual's trajectory of general health status across time. Although it is not possible to fully assess the adequacy of this assumption, we assess the rob ustness of the approach by varying the assumptions underlying the proposed model, such as the random effects distribution and the drop-out component. It appears that between-subject differences in initial functional limitatio n are strongly associated with future functional limitation and that this a ssociation is stronger for those who do not ha re physical activity regardl ess of the random effects and informative dropout specifications. In contra st, the association between current functional limitation and previous traj ectory of functional status within an individual is weaker and more sensiti ve to changes in the random effects and drop-out assumptions.